SpatBox

A Python Library For GeoSpatial Data Proressing and Modeling！

Now it only consists of few tools, we will maintain it and add more geospatial-propressing-tools!

How to install spatbox in your own PC?

We recommend to use the conda to install SpatBox

First, install the anaconda / miniconda in your own computer.

Go to anaconda or miniconda to

download the conda; you can also see my zhihu-blog miniconda安装

Second, create a conda env and install the dependence of SpatBox.

Open the "Anaconda Prompt" and input the code conda create -n spat-env python=3.9, then enter,

After that, activate the conda-env you have created, use conda activate spat-env, and you will get in the "spat-env" conda-env

Then we install the mamba package to get a rapid installation:

conda install -c conda-forge mamba

(if you are in China, you can use conda install mamba -c https://mirrors.sustech.edu.cn/anaconda/cloud/conda-forge)

The SpatBox Library depends on GDAL；Geopandas;rasterio..... , all of the dependence are include in pysal's dependence,

you can use mamba install -c conda-forge pysal to get all of the spatbox dependence installed.

(if you are in China, you can use mamba install pysal -c https://mirrors.sustech.edu.cn/anaconda/cloud/conda-forge)

Finally, install SpatBox.

Input the code pip install spatbox in your "spat-env" conda-env,

(if you are in China, you can use pip install spatbox -i https://pypi.douban.com/simple)

Check Whether the spatbox can work?

Open the Jupyter Notebook or VSCode, run:

import spatbox as stx
import geopandas as gpd
import matplotlib.pyplot as plt  

lp = gpd.read_file(stx.utils.get_path('lp'))

stx.make_grid(inputfile=stx.utils.get_path('lp'),
              outfile='square',
              gridsize=10000,
              square=True)

lp_square = gpd.read_file('square')
fig, ax = plt.subplots(1,1, figsize=(12,9))
lp_square.plot(ax=ax, fc='w', ec='grey') 
lp.plot(ax=ax, fc='none', ec='r')

stx.make_grid(inputfile=stx.utils.get_path('lp'),
              outfile='honeycomb',
              gridsize=10000,
              square=False)

lp_honeycomb = gpd.read_file('honeycomb')
fig, ax = plt.subplots(1,1, figsize=(12,9))
lp_honeycomb.plot(ax=ax, fc='w', ec='grey') 
lp.plot(ax=ax, fc='none', ec='r')